""" Standalone deployment utilities for publishing to HuggingFace Spaces. No Gradio dependencies - can be used in backend API. """ import os import re import json import uuid import tempfile import shutil import ast from typing import Dict, List, Optional, Tuple from pathlib import Path from huggingface_hub import HfApi from backend_models import get_inference_client, get_real_model_id from backend_parsers import ( parse_transformers_js_output, parse_html_code, parse_python_requirements, parse_multi_file_python_output, strip_tool_call_markers, remove_code_block, extract_import_statements, generate_requirements_txt_with_llm ) def prettify_comfyui_json_for_html(json_content: str) -> str: """Convert ComfyUI JSON to stylized HTML display with download button""" try: # Parse and prettify the JSON parsed_json = json.loads(json_content) prettified_json = json.dumps(parsed_json, indent=2, ensure_ascii=False) # Create Apple-style HTML wrapper html_content = f"""
View and download your workflow JSON
{prettified_json}
Error: Invalid JSON format
{json_content}
"""
except Exception as e:
print(f"Error prettifying ComfyUI JSON: {e}")
return json_content
# Note: parse_transformers_js_output, parse_python_requirements, strip_tool_call_markers,
# remove_code_block, extract_import_statements, generate_requirements_txt_with_llm,
# and parse_multi_file_python_output are now imported from backend_parsers.py
def is_streamlit_code(code: str) -> bool:
"""Check if code is Streamlit"""
return 'import streamlit' in code or 'streamlit.run' in code
def is_gradio_code(code: str) -> bool:
"""Check if code is Gradio"""
return 'import gradio' in code or 'gr.' in code
def detect_sdk_from_code(code: str, language: str) -> str:
"""Detect the appropriate SDK from code and language"""
if language == "html":
return "static"
elif language == "transformers.js":
return "static"
elif language == "comfyui":
return "static"
elif language == "react":
return "docker"
elif language == "streamlit" or is_streamlit_code(code):
return "docker"
elif language == "gradio" or is_gradio_code(code):
return "gradio"
else:
return "gradio" # Default
def add_anycoder_tag_to_readme(api, repo_id: str, app_port: Optional[int] = None) -> None:
"""
Download existing README, add anycoder tag and app_port if needed, and upload back.
Preserves all existing README content and frontmatter.
Args:
api: HuggingFace API client
repo_id: Repository ID (username/space-name)
app_port: Optional port number to set for Docker spaces (e.g., 7860)
"""
try:
import tempfile
import re
# Download the existing README
readme_path = api.hf_hub_download(
repo_id=repo_id,
filename="README.md",
repo_type="space"
)
# Read the existing README content
with open(readme_path, 'r', encoding='utf-8') as f:
content = f.read()
# Parse frontmatter and content
if content.startswith('---'):
# Split frontmatter and body
parts = content.split('---', 2)
if len(parts) >= 3:
frontmatter = parts[1].strip()
body = parts[2] if len(parts) > 2 else ""
# Check if tags already exist
if 'tags:' in frontmatter:
# Add anycoder to existing tags if not present
if '- anycoder' not in frontmatter:
frontmatter = re.sub(r'(tags:\s*\n(?:\s*-\s*[^\n]+\n)*)', r'\1- anycoder\n', frontmatter)
else:
# Add tags section with anycoder
frontmatter += '\ntags:\n- anycoder'
# Add app_port if specified and not already present
if app_port is not None and 'app_port:' not in frontmatter:
frontmatter += f'\napp_port: {app_port}'
# Reconstruct the README
new_content = f"---\n{frontmatter}\n---{body}"
else:
# Malformed frontmatter, just add tags at the end of frontmatter
new_content = content.replace('---', '---\ntags:\n- anycoder\n---', 1)
else:
# No frontmatter, add it at the beginning
app_port_line = f'\napp_port: {app_port}' if app_port else ''
new_content = f"---\ntags:\n- anycoder{app_port_line}\n---\n\n{content}"
# Upload the modified README
with tempfile.NamedTemporaryFile("w", suffix=".md", delete=False, encoding='utf-8') as f:
f.write(new_content)
temp_path = f.name
api.upload_file(
path_or_fileobj=temp_path,
path_in_repo="README.md",
repo_id=repo_id,
repo_type="space"
)
os.unlink(temp_path)
except Exception as e:
print(f"Warning: Could not modify README.md to add anycoder tag: {e}")
def create_dockerfile_for_streamlit(space_name: str) -> str:
"""Create Dockerfile for Streamlit app"""
return f"""FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
EXPOSE 7860
CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0"]
"""
def create_dockerfile_for_react(space_name: str) -> str:
"""Create Dockerfile for React app"""
return f"""FROM node:18-slim
# Use existing node user
USER node
ENV HOME=/home/node
ENV PATH=/home/node/.local/bin:$PATH
WORKDIR /home/node/app
COPY --chown=node:node package*.json ./
RUN npm install
COPY --chown=node:node . .
RUN npm run build
EXPOSE 7860
CMD ["npm", "start", "--", "-p", "7860"]
"""
def extract_space_id_from_history(history: Optional[List[Dict]], username: Optional[str] = None) -> Optional[str]:
"""
Extract existing space ID from chat history (for updates after followups/imports)
Args:
history: Chat history (list of dicts with 'role' and 'content')
username: Current username (to verify ownership of imported spaces)
Returns:
Space ID (username/space-name) if found, None otherwise
"""
if not history:
return None
import re
existing_space = None
# Look through history for previous deployments or imports
for msg in history:
role = msg.get('role', '')
content = msg.get('content', '')
# Check assistant messages for deployment confirmations
if role == 'assistant':
if "✅ Deployed!" in content or "✅ Updated!" in content:
# Look for space URL pattern
match = re.search(r'huggingface\.co/spaces/([^/\s\)]+/[^/\s\)]+)', content)
if match:
existing_space = match.group(1)
break
# Check user messages for imports
elif role == 'user':
if "import" in content.lower() and "space" in content.lower():
# Extract space name from import message
match = re.search(r'huggingface\.co/spaces/([^/\s\)]+/[^/\s\)]+)', content)
if match:
imported_space = match.group(1)
# Only use imported space if user owns it (can update it)
if username and imported_space.startswith(f"{username}/"):
existing_space = imported_space
break
# If user doesn't own the imported space, we'll create a new one
# (existing_space remains None, triggering new deployment)
return existing_space
def deploy_to_huggingface_space(
code: str,
language: str,
space_name: Optional[str] = None,
token: Optional[str] = None,
username: Optional[str] = None,
description: Optional[str] = None,
private: bool = False,
existing_repo_id: Optional[str] = None,
commit_message: Optional[str] = None,
history: Optional[List[Dict]] = None
) -> Tuple[bool, str, Optional[str]]:
"""
Deploy code to HuggingFace Spaces (create new or update existing)
Args:
code: Generated code to deploy
language: Target language/framework (html, gradio, streamlit, react, transformers.js, comfyui)
space_name: Name for the space (auto-generated if None, ignored if existing_repo_id provided)
token: HuggingFace API token
username: HuggingFace username
description: Space description
private: Whether to make the space private (only for new spaces)
existing_repo_id: If provided (username/space-name), updates this space instead of creating new one
commit_message: Custom commit message (defaults to "Deploy from anycoder" or "Update from anycoder")
history: Chat history (list of dicts with 'role' and 'content') - used to detect followups/imports
Returns:
Tuple of (success: bool, message: str, space_url: Optional[str])
"""
if not token:
token = os.getenv("HF_TOKEN")
if not token:
return False, "No HuggingFace token provided", None
try:
api = HfApi(token=token)
# Get username if not provided (needed for history tracking)
if not username:
try:
user_info = api.whoami()
username = user_info.get("name") or user_info.get("preferred_username") or "user"
except Exception as e:
pass # Will handle later if needed
# Check history for existing space if not explicitly provided
# This enables automatic updates for followup prompts and imported spaces
if not existing_repo_id and history:
existing_repo_id = extract_space_id_from_history(history, username)
if existing_repo_id:
print(f"[Deploy] Detected existing space from history: {existing_repo_id}")
# Determine if this is an update or new deployment
is_update = existing_repo_id is not None
print(f"[Deploy] ========== DEPLOYMENT DECISION ==========")
print(f"[Deploy] existing_repo_id provided: {existing_repo_id}")
print(f"[Deploy] history provided: {history is not None} (length: {len(history) if history else 0})")
print(f"[Deploy] username: {username}")
print(f"[Deploy] is_update: {is_update}")
print(f"[Deploy] ============================================")
if is_update:
# Use existing repo
repo_id = existing_repo_id
space_name = existing_repo_id.split('/')[-1]
if '/' in existing_repo_id:
username = existing_repo_id.split('/')[0]
elif not username:
# Get username if still not available
try:
user_info = api.whoami()
username = user_info.get("name") or user_info.get("preferred_username") or "user"
except Exception as e:
return False, f"Failed to get user info: {str(e)}", None
else:
# Get username if not provided
if not username:
try:
user_info = api.whoami()
username = user_info.get("name") or user_info.get("preferred_username") or "user"
except Exception as e:
return False, f"Failed to get user info: {str(e)}", None
# Generate space name if not provided or empty
if not space_name or space_name.strip() == "":
space_name = f"anycoder-{uuid.uuid4().hex[:8]}"
print(f"[Deploy] Auto-generated space name: {space_name}")
# Clean space name (no spaces, lowercase, alphanumeric + hyphens)
space_name = re.sub(r'[^a-z0-9-]', '-', space_name.lower())
space_name = re.sub(r'-+', '-', space_name).strip('-')
# Ensure space_name is not empty after cleaning
if not space_name:
space_name = f"anycoder-{uuid.uuid4().hex[:8]}"
print(f"[Deploy] Space name was empty after cleaning, regenerated: {space_name}")
repo_id = f"{username}/{space_name}"
print(f"[Deploy] Using repo_id: {repo_id}")
# Detect SDK
sdk = detect_sdk_from_code(code, language)
# Create temporary directory for files
with tempfile.TemporaryDirectory() as temp_dir:
temp_path = Path(temp_dir)
# Parse code based on language
app_port = None # Track if we need app_port for Docker spaces
use_individual_uploads = False # Flag for transformers.js
if language == "transformers.js":
try:
files = parse_transformers_js_output(code)
print(f"[Deploy] Parsed transformers.js files: {list(files.keys())}")
# Log file sizes for debugging
for fname, fcontent in files.items():
if fcontent:
print(f"[Deploy] {fname}: {len(fcontent)} characters")
else:
print(f"[Deploy] {fname}: EMPTY")
# Validate all three files are present in the dict
required_files = {'index.html', 'index.js', 'style.css'}
missing_from_dict = required_files - set(files.keys())
if missing_from_dict:
error_msg = f"Failed to parse required files: {', '.join(sorted(missing_from_dict))}. "
error_msg += f"Parsed files: {', '.join(files.keys()) if files else 'none'}. "
error_msg += "Transformers.js apps require all three files (index.html, index.js, style.css). Please regenerate using the correct format."
print(f"[Deploy] {error_msg}")
return False, error_msg, None
# Validate files have actual content (not empty or whitespace-only)
empty_files = [name for name in required_files if not files.get(name, '').strip()]
if empty_files:
error_msg = f"Empty file content detected: {', '.join(sorted(empty_files))}. "
error_msg += "All three files must contain actual code. Please regenerate with complete content."
print(f"[Deploy] {error_msg}")
return False, error_msg, None
# Write transformers.js files to temp directory
for filename, content in files.items():
file_path = temp_path / filename
print(f"[Deploy] Writing {filename} ({len(content)} chars) to {file_path}")
# Use text mode - Python handles encoding automatically
file_path.write_text(content, encoding='utf-8')
# Verify the write was successful
written_size = file_path.stat().st_size
print(f"[Deploy] Verified {filename}: {written_size} bytes on disk")
# For transformers.js, we'll upload files individually (not via upload_folder)
use_individual_uploads = True
except Exception as e:
print(f"[Deploy] Error parsing transformers.js: {e}")
import traceback
traceback.print_exc()
return False, f"Error parsing transformers.js output: {str(e)}", None
elif language == "html":
html_code = parse_html_code(code)
(temp_path / "index.html").write_text(html_code, encoding='utf-8')
elif language == "comfyui":
# ComfyUI is JSON, wrap in stylized HTML viewer with download button
html_code = prettify_comfyui_json_for_html(code)
(temp_path / "index.html").write_text(html_code, encoding='utf-8')
elif language in ["gradio", "streamlit"]:
files = parse_multi_file_python_output(code)
# Write Python files (create subdirectories if needed)
for filename, content in files.items():
file_path = temp_path / filename
file_path.parent.mkdir(parents=True, exist_ok=True)
file_path.write_text(content, encoding='utf-8')
# Ensure requirements.txt exists - generate from imports if missing
if "requirements.txt" not in files:
# Get the main app file (app.py for gradio, streamlit_app.py or app.py for streamlit)
main_app = files.get('streamlit_app.py') or files.get('app.py', '')
if main_app:
print(f"[Deploy] Generating requirements.txt from imports in {language} app")
import_statements = extract_import_statements(main_app)
requirements_content = generate_requirements_txt_with_llm(import_statements)
(temp_path / "requirements.txt").write_text(requirements_content, encoding='utf-8')
print(f"[Deploy] Generated requirements.txt with {len(requirements_content.splitlines())} lines")
else:
# Fallback to minimal requirements if no app file found
if language == "gradio":
(temp_path / "requirements.txt").write_text("gradio>=4.0.0\n", encoding='utf-8')
elif language == "streamlit":
(temp_path / "requirements.txt").write_text("streamlit>=1.30.0\n", encoding='utf-8')
# Create Dockerfile if needed
if sdk == "docker":
if language == "streamlit":
dockerfile = create_dockerfile_for_streamlit(space_name)
(temp_path / "Dockerfile").write_text(dockerfile, encoding='utf-8')
app_port = 7860 # Set app_port for Docker spaces
use_individual_uploads = True # Streamlit uses individual file uploads
elif language == "react":
# Parse React output to get all files (uses same multi-file format as Python)
files = parse_multi_file_python_output(code)
if not files:
return False, "Error: Could not parse React output", None
# If Dockerfile is missing, use template
if 'Dockerfile' not in files:
dockerfile = create_dockerfile_for_react(space_name)
files['Dockerfile'] = dockerfile
# Write all React files (create subdirectories if needed)
for filename, content in files.items():
file_path = temp_path / filename
file_path.parent.mkdir(parents=True, exist_ok=True)
file_path.write_text(content, encoding='utf-8')
app_port = 7860 # Set app_port for Docker spaces
use_individual_uploads = True # React uses individual file uploads
else:
# Default: treat as Gradio app
files = parse_multi_file_python_output(code)
# Write files (create subdirectories if needed)
for filename, content in files.items():
file_path = temp_path / filename
file_path.parent.mkdir(parents=True, exist_ok=True)
file_path.write_text(content, encoding='utf-8')
# Generate requirements.txt from imports if missing
if "requirements.txt" not in files:
main_app = files.get('app.py', '')
if main_app:
print(f"[Deploy] Generating requirements.txt from imports in default app")
import_statements = extract_import_statements(main_app)
requirements_content = generate_requirements_txt_with_llm(import_statements)
(temp_path / "requirements.txt").write_text(requirements_content, encoding='utf-8')
print(f"[Deploy] Generated requirements.txt with {len(requirements_content.splitlines())} lines")
else:
# Fallback to minimal requirements if no app file found
(temp_path / "requirements.txt").write_text("gradio>=4.0.0\n", encoding='utf-8')
# Don't create README - HuggingFace will auto-generate it
# We'll add the anycoder tag after deployment
# ONLY create repo for NEW deployments of non-Docker, non-transformers.js spaces
# Docker and transformers.js handle repo creation separately below
# This matches the Gradio version logic (line 1256 in ui.py)
if not is_update and sdk != "docker" and language not in ["transformers.js"]:
print(f"[Deploy] Creating NEW {sdk} space: {repo_id}")
try:
api.create_repo(
repo_id=repo_id,
repo_type="space",
space_sdk=sdk,
private=private,
exist_ok=True
)
except Exception as e:
return False, f"Failed to create space: {str(e)}", None
elif is_update:
print(f"[Deploy] UPDATING existing space: {repo_id} (skipping create_repo)")
# Handle transformers.js spaces (create repo via duplicate_space)
if language == "transformers.js":
if not is_update:
print(f"[Deploy] Creating NEW transformers.js space via template duplication")
print(f"[Deploy] space_name value: '{space_name}' (type: {type(space_name)})")
# Safety check for space_name
if not space_name:
return False, "Internal error: space_name is None after generation", None
try:
from huggingface_hub import duplicate_space
# duplicate_space expects just the space name (not full repo_id)
# Use strip() to clean the space name
clean_space_name = space_name.strip()
print(f"[Deploy] Attempting to duplicate template space to: {clean_space_name}")
duplicated_repo = duplicate_space(
from_id="static-templates/transformers.js",
to_id=clean_space_name,
token=token,
exist_ok=True
)
print(f"[Deploy] Template duplication result: {duplicated_repo} (type: {type(duplicated_repo)})")
except Exception as e:
print(f"[Deploy] Exception during duplicate_space: {type(e).__name__}: {str(e)}")
# Check if space actually exists (success despite error)
space_exists = False
try:
if api.space_info(repo_id):
space_exists = True
except:
pass
# Handle RepoUrl object "errors"
error_msg = str(e)
if ("'url'" in error_msg or "RepoUrl" in error_msg) and space_exists:
print(f"[Deploy] Space exists despite RepoUrl error, continuing with deployment")
else:
# Fallback to regular create_repo
print(f"[Deploy] Template duplication failed, attempting fallback to create_repo: {e}")
try:
api.create_repo(
repo_id=repo_id,
repo_type="space",
space_sdk="static",
private=private,
exist_ok=True
)
print(f"[Deploy] Fallback create_repo successful")
except Exception as e2:
return False, f"Failed to create transformers.js space (both duplication and fallback failed): {str(e2)}", None
else:
# For updates, verify we can access the existing space
try:
space_info = api.space_info(repo_id)
if not space_info:
return False, f"Could not access space {repo_id} for update", None
except Exception as e:
return False, f"Cannot update space {repo_id}: {str(e)}", None
# Handle Docker spaces (React/Streamlit) - create repo separately
elif sdk == "docker" and language in ["streamlit", "react"]:
if not is_update:
print(f"[Deploy] Creating NEW Docker space for {language}: {repo_id}")
try:
from huggingface_hub import create_repo as hf_create_repo
hf_create_repo(
repo_id=repo_id,
repo_type="space",
space_sdk="docker",
token=token,
exist_ok=True
)
except Exception as e:
return False, f"Failed to create Docker space: {str(e)}", None
# Upload files
if not commit_message:
commit_message = "Update from anycoder" if is_update else "Deploy from anycoder"
try:
if language == "transformers.js":
# Special handling for transformers.js - create NEW temp files for each upload
# This matches the working pattern in ui.py
import time
# Get the parsed files from earlier
files_to_upload = [
("index.html", files.get('index.html')),
("index.js", files.get('index.js')),
("style.css", files.get('style.css'))
]
max_attempts = 3
for file_name, file_content in files_to_upload:
if not file_content:
return False, f"Missing content for {file_name}", None
success = False
last_error = None
for attempt in range(max_attempts):
temp_file_path = None
try:
# Create a NEW temp file for this upload (matches Gradio version approach)
print(f"[Deploy] Creating temp file for {file_name} with {len(file_content)} chars")
# Use text mode "w" - lets Python handle encoding automatically (better emoji support)
with tempfile.NamedTemporaryFile("w", suffix=f".{file_name.split('.')[-1]}", delete=False) as f:
f.write(file_content)
temp_file_path = f.name
# File is now closed and flushed, safe to upload
# Upload the file without commit_message (HF handles this for spaces)
api.upload_file(
path_or_fileobj=temp_file_path,
path_in_repo=file_name,
repo_id=repo_id,
repo_type="space"
)
success = True
print(f"[Deploy] Successfully uploaded {file_name}")
break
except Exception as e:
last_error = e
error_str = str(e)
print(f"[Deploy] Upload error for {file_name}: {error_str}")
if "403" in error_str or "Forbidden" in error_str:
return False, f"Permission denied uploading {file_name}. Check your token has write access to {repo_id}.", None
if attempt < max_attempts - 1:
time.sleep(2) # Wait before retry
print(f"[Deploy] Retry {attempt + 1}/{max_attempts} for {file_name}")
finally:
# Clean up temp file
if temp_file_path and os.path.exists(temp_file_path):
os.unlink(temp_file_path)
if not success:
return False, f"Failed to upload {file_name} after {max_attempts} attempts: {last_error}", None
elif use_individual_uploads:
# For React, Streamlit: upload each file individually
import time
# Get list of files to upload from temp directory
files_to_upload = []
for file_path in temp_path.rglob('*'):
if file_path.is_file():
# Get relative path from temp directory (use forward slashes for repo paths)
rel_path = file_path.relative_to(temp_path)
files_to_upload.append(str(rel_path).replace('\\', '/'))
if not files_to_upload:
return False, "No files to upload", None
print(f"[Deploy] Uploading {len(files_to_upload)} files individually: {files_to_upload}")
max_attempts = 3
for filename in files_to_upload:
# Convert back to Path for filesystem operations
file_path = temp_path / filename.replace('/', os.sep)
if not file_path.exists():
return False, f"Failed to upload: {filename} not found", None
# Upload with retry logic
success = False
last_error = None
for attempt in range(max_attempts):
try:
# Upload without commit_message - HF API handles this for spaces
api.upload_file(
path_or_fileobj=str(file_path),
path_in_repo=filename,
repo_id=repo_id,
repo_type="space"
)
success = True
print(f"[Deploy] Successfully uploaded {filename}")
break
except Exception as e:
last_error = e
error_str = str(e)
print(f"[Deploy] Upload error for {filename}: {error_str}")
if "403" in error_str or "Forbidden" in error_str:
return False, f"Permission denied uploading {filename}. Check your token has write access to {repo_id}.", None
if attempt < max_attempts - 1:
time.sleep(2) # Wait before retry
print(f"[Deploy] Retry {attempt + 1}/{max_attempts} for {filename}")
if not success:
return False, f"Failed to upload {filename} after {max_attempts} attempts: {last_error}", None
else:
# For other languages, use upload_folder
print(f"[Deploy] Uploading folder to {repo_id}")
api.upload_folder(
folder_path=str(temp_path),
repo_id=repo_id,
repo_type="space"
)
except Exception as e:
return False, f"Failed to upload files: {str(e)}", None
# After successful upload, modify the auto-generated README to add anycoder tag
# For new spaces: HF auto-generates README, wait and modify it
# For updates: README should already exist, just add tag if missing
try:
import time
if not is_update:
time.sleep(2) # Give HF time to generate README for new spaces
add_anycoder_tag_to_readme(api, repo_id, app_port)
except Exception as e:
# Don't fail deployment if README modification fails
print(f"Warning: Could not add anycoder tag to README: {e}")
# For transformers.js updates, trigger a space restart to ensure changes take effect
if is_update and language == "transformers.js":
try:
api.restart_space(repo_id=repo_id)
print(f"[Deploy] Restarted space after update: {repo_id}")
except Exception as restart_error:
# Don't fail the deployment if restart fails, just log it
print(f"Note: Could not restart space after update: {restart_error}")
space_url = f"https://huggingface.co/spaces/{repo_id}"
action = "Updated" if is_update else "Deployed"
# Include the space URL in the message for history tracking
# This allows future deployments to detect this as the existing space
success_msg = f"✅ {action}! View your space at: {space_url}"
return True, success_msg, space_url
except Exception as e:
print(f"[Deploy] Top-level exception caught: {type(e).__name__}: {str(e)}")
import traceback
traceback.print_exc()
return False, f"Deployment error: {str(e)}", None
def update_space_file(
repo_id: str,
file_path: str,
content: str,
token: Optional[str] = None,
commit_message: Optional[str] = None
) -> Tuple[bool, str]:
"""
Update a single file in an existing HuggingFace Space
Args:
repo_id: Full repo ID (username/space-name)
file_path: Path of file to update (e.g., "app.py")
content: New file content
token: HuggingFace API token
commit_message: Commit message (default: "Update {file_path}")
Returns:
Tuple of (success: bool, message: str)
"""
if not token:
token = os.getenv("HF_TOKEN")
if not token:
return False, "No HuggingFace token provided"
try:
api = HfApi(token=token)
if not commit_message:
commit_message = f"Update {file_path}"
# Create temporary file
with tempfile.NamedTemporaryFile(mode='w', suffix=f'.{file_path.split(".")[-1]}', delete=False) as f:
f.write(content)
temp_path = f.name
try:
api.upload_file(
path_or_fileobj=temp_path,
path_in_repo=file_path,
repo_id=repo_id,
repo_type="space",
commit_message=commit_message
)
return True, f"✅ Successfully updated {file_path}"
finally:
os.unlink(temp_path)
except Exception as e:
return False, f"Failed to update file: {str(e)}"
def delete_space(
repo_id: str,
token: Optional[str] = None
) -> Tuple[bool, str]:
"""
Delete a HuggingFace Space
Args:
repo_id: Full repo ID (username/space-name)
token: HuggingFace API token
Returns:
Tuple of (success: bool, message: str)
"""
if not token:
token = os.getenv("HF_TOKEN")
if not token:
return False, "No HuggingFace token provided"
try:
api = HfApi(token=token)
api.delete_repo(repo_id=repo_id, repo_type="space")
return True, f"✅ Successfully deleted {repo_id}"
except Exception as e:
return False, f"Failed to delete space: {str(e)}"
def list_user_spaces(
username: Optional[str] = None,
token: Optional[str] = None
) -> Tuple[bool, str, Optional[List[Dict]]]:
"""
List all spaces for a user
Args:
username: HuggingFace username (gets from token if None)
token: HuggingFace API token
Returns:
Tuple of (success: bool, message: str, spaces: Optional[List[Dict]])
"""
if not token:
token = os.getenv("HF_TOKEN")
if not token:
return False, "No HuggingFace token provided", None
try:
api = HfApi(token=token)
# Get username if not provided
if not username:
user_info = api.whoami()
username = user_info.get("name") or user_info.get("preferred_username")
# List spaces
spaces = api.list_spaces(author=username)
space_list = []
for space in spaces:
space_list.append({
"id": space.id,
"author": space.author,
"name": getattr(space, 'name', space.id.split('/')[-1]),
"sdk": getattr(space, 'sdk', 'unknown'),
"private": getattr(space, 'private', False),
"url": f"https://huggingface.co/spaces/{space.id}"
})
return True, f"Found {len(space_list)} spaces", space_list
except Exception as e:
return False, f"Failed to list spaces: {str(e)}", None